Pengembangan Model Pendeteksian Gambar Rambu Lalu Lintas dengan Metode Faster R-CNN dengan Library Tensorflow

Abstrak

This study aims to develop a machine learning model to detect blocked traffic signals using the faster R-CNN method. Traffic signal detection is the most important part of a traffic unit. To solve this problem, the detection method relies on deep learning. The method used in this study is an image processing technique in which there is a faster R-CNN using additional stages of the search process. This research resulted in the development of a traffic light image detection model using the faster R-CNN method with a tensorflow library of traffic sign detection.